Offer summary

Qualifications:

Bachelor's or Master's degree in Computer Science, Engineering, or a related field., 7+ years of experience in data engineering, particularly with Databricks and Spark., Deep understanding of data warehousing concepts and ETL/ELT workflows., Strong programming skills in Python and SQL, with experience in cloud platforms like AWS or GCP..

Key responsabilities:

Design, develop, and optimize data pipelines using Databricks for large-scale data processing.

Collaborate with Tech Leads and Product Managers to integrate and transform data from various sources.

Develop and maintain high-quality Databricks workflows for analytics and reporting.

Monitor and improve data quality and reliability across data systems, driving best practices in data engineering.

Job description

Data Engineer Databricks | Retail Industry

Were looking for an experienced Data Engineer with strong hands-on expertise in Databricks to join our team and support key initiatives in the Retail sector. Youll be responsible for building and maintaining scalable, high-performance data solutions that help drive intelligent decision-making across the business.

If you thrive working with large datasets, love building robust pipelines, and have a passion for solving complex problems in the retail worldthis role is for you.

What Youll Do:

Design, develop, and optimize data pipelines using Databricks to support large-scale data processing and analytics.
Collaborate with Tech Leads, Product Managers, and fellow Engineers to integrate and transform data from multiple sources (structured and unstructured).
Develop and maintain high-quality, production-grade Databricks workflows to support analytics, reporting, and machine learning initiatives.
Ensure all solutions are built with scalability, performance, and cost-efficiency in mind, tailored to retail-specific needs like sales, inventory, and customer behavior.
Monitor and improve data quality, reliability, and observability across data systems.
Drive best practices in data engineering, automation, and continuous improvement.

What Were Looking For:

Bachelors or Masters degree in Computer Science, Engineering, or related field.
7+ years of experience in data engineering, with a proven track record in Databricks and Spark.
Deep understanding of data warehousing concepts, data lake architecture, and ETL/ELT workflows.
Hands-on experience with cloud platforms such as AWS or GCP.
Experience working with retail datasets: transactions, supply chain, point-of-sale systems, etc.
Strong experience with orchestration tools like Apache Airflow.
Solid programming skills in Python and SQL.
Ability to work collaboratively in cross-functional teams, with clear communication and a problem-solving mindset.

¡Postulate ahora y sumate a la querida Darwoft!
talento@darwoft.com
Consultas? Sigue al Recruiter

https://www.linkedin.com/in/hernanvietto/